![[2601.10161] AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2601.10161] AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers
Summary
AWED-FiNER introduces an innovative tool for Fine-grained Named Entity Recognition (FgNER) across 36 languages, enhancing NLP capabilities for over 6.6 billion speakers.
Why It Matters
This research addresses the critical need for effective Named Entity Recognition in diverse languages, particularly for low-resource languages. By providing open-source tools and expert models, it democratizes access to advanced NLP technologies, enabling broader applications in semantic search and information retrieval.
Key Takeaways
- AWED-FiNER offers a multilingual FgNER solution for 36 languages.
- The platform includes an agentic tool and web application for easy access.
- It supports both high-resource and low-resource languages, enhancing inclusivity.
- 53 expert models are available for offline deployment, useful in resource-constrained environments.
- The initiative aims to improve semantic search and structured data extraction globally.
Computer Science > Computation and Language arXiv:2601.10161 (cs) [Submitted on 15 Jan 2026 (v1), last revised 20 Feb 2026 (this version, v2)] Title:AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers Authors:Prachuryya Kaushik, Ashish Anand View a PDF of the paper titled AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers, by Prachuryya Kaushik and Ashish Anand View PDF HTML (experimental) Abstract:Named Entity Recognition (NER) is a foundational task in Natural Language Processing (NLP) and Information Retrieval (IR), which facilitates semantic search and structured data extraction. We introduce \textbf{AWED-FiNER}, an open-source collection of agentic tool, web application, and 53 state-of-the-art expert models that provide Fine-grained Named Entity Recognition (FgNER) solutions across 36 languages spoken by more than 6.6 billion people. The agentic tool enables routing multilingual text to specialized expert models to fetch FgNER annotations within seconds. The web-based platform provides a ready-to-use FgNER annotation service for non-technical users. Moreover, the collection of language-specific extremely small open-source state-of-the-art expert models facilitates offline deployment in resource-constrained scenarios, including edge devices. AWED-FiNER covers languages spoken by ove...
